Constrained observability techniques for structural system identification using modal analysis

Abstract

The characteristics of civil structures inevitably suffer a certain level of damage during its lifetime and cheap, non-destructive and reliable methods to assess their correct performance are of high importance. Structural System Identification (SSI) using measured response is the way to fine why performance is not correct and identify where the problems can be found. Different methods of SSI exist, both using static and vibration experimental data. However, using these methods is not always possible to decide if available measurements are sufficient to uniquely obtain the unknown. A (SSI) method that uses constrained observability method (COM) has already been developed based on the information provided by the monitoring of static non-destructive tests -using deflections and rotations under a known loading case. The method assures that all observable variables can be obtained with the available measured data. In the present paper, the problem of determining the actual characteristics of the members of a structure such as axial stiffness, flexural stiffness and mass using vibration data is analyzed. Subsets of natural frequencies and/or modal shapes are used. To give a better understanding of the proposed method and to demonstrate its potential applicability, several examples of growing complexity are analyzed, and the results show how constrained observability techniques might be efficiently used for the dynamic identification of structural systems using dynamic data. These lead to significant conclusions regarding the functioning of an SSI method based on dynamic behavior.

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

“…In this paper, the effect of weighting factors was ignored. The specific implementation steps can be found in the literature [ 11 ].…”

“…The 5% and 95% percentages of the normalized values of EI 2 and EI 3 were [0.684, 1.312] and [0.608, 1.383], respectively. In absolute terms, EI 2 will be in the range of [5.57, 10.68]×10 11 and EI 3 in [4.96, 11.27]×10 11 within 95% confidence interval. It can be seen that the output variable EI 2 exhibited less uncertainty.…”

“…This mathematical approach has been applied as a static SSI method [ 5 , 6 , 7 , 8 ]. The numerical OM [ 9 ] and constrained observability method (COM) [ 10 , 11 ] were developed based on the observability method for the static and dynamic analysis. In order to obtain accurate and reliable parameters, OM identification needs to be robust in terms of variations of systematic modeling uncertainty introduced when modeling complex systems and measurement uncertainty caused by the quality of test equipment and the accuracy of the sensors [ 12 ].…”

New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings

“…This procedure uses the members' stiffness relations for computing internal forces and nodal displacements by equilibrium and stiffness equations. On the other hand, for a dynamic simulation, students are usually introduced to a modal analysis procedure [3]. In this matrix method, the equations are considered a dynamic spring mass system, where eigenvalue analysis provides information of both the frequencies and mode shapes of the structure.…”

New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings

“…This procedure uses the members' stiffness relations for computing internal forces and nodal displacements by equilibrium and stiffness equations. On the other hand, for a dynamic simulation, students are usually introduced into modal analysis procedure (Peng et al 2019). In this matrix method, the equations are as a dynamic spring mass system, where eigenvalue analysis provides information of both the frequencies and mode shapes of the structure.…”